Month: November 2019

The tragedy of the commons was a term popularized by Garrett Hardin that illustrated how a group of dependent actors could end up destroying the resources they’d all relied upon due to being driven by their own self-interest. As potential solutions to the issue of resource depletion, Hardin proposes systems of governance or privatization. While human beings have the outstanding capacity for negotiation, social conventions and moral frameworks to potentially curb such tragedies, evolutionary biologists have come to question how non-human organisms would go about doing the same. Consequently, researchers have attempted to apply the tragedy of the commons to a vast array of biological systems to discover the various different mechanisms in play, such as kinship, policing and more.

In Hardin’s paper, he describes a situation where herders would share a plot of land to graze their cattle. While they have the option to graze smaller amounts to sustain their respective cattle for a lifetime, their self-driven interests cause each player to add more cattle to their herd, ultimately resulting in the depletion of land and a losing situation for everyone. This occurs since there is a clear monetary incentive for each individual herder while the losses in environmental stability are felt system wide. These behaviours have been consistently replicated in studies using various natural resources such as marine goods, clean air and more. The wisdom gained from these studies has generally pointed towards some form of negotiation or repercussions on noncompliant actors being needed to prevent a tragedy from occurring. For example, taxing parties that pollute excessively to help prevent ecological waste.

Obviously, these intricate solutions cannot be applied to non-human organisms. In spite of various organisms’ lack of cognitive abilities, however, evolutionary biologists have found mechanisms that they’ll use to circumvent tragedies. For example, kin selection is used by plants in competition for water sources to prevent resource depletion. Additionally, chimpanzees will use dominance-based monopolization strategies along with social tolerance. Punishment is a strategy employed by sea slugs to ensure male slugs are an available resource for reproduction. Non-human organisms have plenty of strategies to employ to avoid a losing situation.

The tragedy of the commons clearly showcases how simply acting in one’s own self-interest can produce heavily negative outcomes in the long run. While it might seem that organisms should be quite susceptible to this tragedy given their self-interested nature and lack of cognitive faculties, it is interesting to see the mechanisms in play to prove the contrary.  One should note that it would be impossible to record organisms that have suffered due to the tragedy as those would no longer exist.

I found this to be an engaging topic of inquiry as the tragedy of the commons has also been conveyed by the Prisoner’s Dilemma that we discussed in lecture. Due to the respective prisoners’ self-interests, both parties end up confessing and face the most possible time in jail as a result. It was interesting to see how evolutionary biologists utilize game theory to develop working models and use them to answer questions regarding evolutionary behaviour.

Relevant Links:

The Tragedy of the Commons in Evolutionary Biology
https://www.sciencedirect.com/science/article/pii/S0169534707002741#tbl1

Koomen, R., & Herrmann, E. (2018). Chimpanzees overcome the tragedy of the commons with dominance. Scientific Reports, 8(1). doi: 10.1038/s41598-018-28416-8

Chimpanzees Overcome the Tragedy of the Commons with Dominance
https://www.nature.com/articles/s41598-018-28416-8#Sec18

Rankin, D. J., Bargum, K., & Kokko, H. (2007). The tragedy of the commons in evolutionary biology. Trends in Ecology & Evolution, 22(12), 643–651. doi: 10.1016/j.tree.2007.07.009

Nash equilibrium and the dominant strategy are standard concepts used to explain game analysis in game theory and is used in many different areas of academic disciplines, such as economics and legal theory.

In the field of construction, game theory has been increasingly applied to analyse a wide variety of problems. Some examples include wage negotiations and optimization of investment projects. In particular, there was a study done on how game theory could be used to help indicate the best winning strategy in court cases between a general contractor (GC) and an investor (IN). The case study is based on a real situation that has happened between two companies in Europe and is going to be analyzed from the GC’s perspective, the party that brought the case to court.

Analogous to choosing strategy A or B in the picture above, both parties GC and IN may take an aggressive approach or a conciliatory strategy in court.

• An aggressive approach is more costly as a lot of resources are going to be used to actively search for opponent’s weaknesses
• A conciliatory approach costs less as it involves searching for a rational compromise and a shorter litigation.

The nitty gritty details about the costs (negative numbers) were based off of the real scenario and can be explained in the linked article, but to summarize, both parties would want to aim for a higher payout.

Additionally, it is realistic to also consider how payoffs and strategies would change depending on court rulings. In the study, it was equally probable for the court to either rule in favour of the GC or the IN. Therefore, two different analysis per court ruling using the Nash equilibrium concept and dominant strategy concept were made. 

Nash Equilibrium for image Table 3, is if GC applies Aggressive Strategy and IN applies Conciliatory Strategy.

Nash Equilibrium for image Table 4, is if GC applies Conciliatory Strategy and IN applies Conciliatory Strategy.

Considering both payoff tables, the IN should apply the conciliatory strategy. It is a more complex answer for what GC should do as different court rulings would impact their strategy. In the case of when the court favours GC, it is best for GC to be aggressive. However, if the ruling is favouring IN, the only strategy for GC to have a positive payoff is conciliatory. 

Although there is not a clear answer as to what GC must always do, it is reasonable to take into other factors on a case to case basis. Depending on how strongly prepared GC is for the court case (concrete evidence, lots of witnesses, expert assessments) or perhaps how ill prepared IN is, if it can be calculated that there is at least a 0.69 probability that such factors will have an impactful influence in the court ruling, then the aggressive strategy is effective. 

The Nash equilibrium and dominant strategy is not only discussed in CSCC46 but also in many areas of study when game theory is often used to analyze scenarios. As discussed in class, the dominant strategy was used here in this scenario to help explain situations where the two parties (GC and IN in this case) might have more of an incentive to choose one option over another. This article provides a real world insight of how such a strategy can be useful for both opponents. In the case of the IN, they are always going to try to minimize their loss whereas in the case of GC, their optimal strategy will depend on the predictions on whether or not the court will rule in their favour. The article discusses other factors to consider, such as when further analysis needs to be done depending on “game states” which was, in the article, the side the court could choose to favour. Despite such thorough analysis, it was also highlighted that legal action should be the last option GC should try to resolve conflicts as there are less expensive alternatives such as mediation. However, if it ever did get to the point of bringing the investors to court, game theory would play an important role in choosing a winning strategy.

References:

Grzyl, B., Apollo, M., & Kristowski, A. (2019). Application of Game Theory to Conflict Management in a Construction Contract. Sustainability, 11(7), 1983. doi: 10.3390/su11071983

Mentioned Blog:

https://www.investopedia.com/terms/n/nash-equilibrium.asp

Recently in the Washington State University, researchers have created a new method to identify antimicrobial-resistance (AMR). The new method uses game theory to choose the important features to be used in their machine learning model. While there were many attempts in identifying AMR with machine learning, there was never a good strategy to identify the important features to be used. 

Most of the strategies used in the past had either resulted in high computational overhead or low accuracy. However researchers found out using game theory they can now include features that are poorly predictive as single variables, which are traditionally rejected. The method uses the behavior of different features and consider how they behave together as a whole. Using the data generated from game theory, they can then train their machine learning model to accurately predict AMR. The resulting algorithm has an accuracy ranging from 93% – 99% as shown in the figure below. 

“This novel game theory approach is especially powerful because features are chosen on the basis of how well they work together as a whole to identify likely antimicrobial-resistance genes — taking into account both the relevance and interdependency of features,” – Broschat, one of the researchers in developing this new method of identifying AMR.

Source:
Abu Sayed Chowdhury, Douglas R. Call, Shira L. Broschat. Antimicrobial Resistance Prediction for Gram-Negative Bacteria via Game Theory-Based Feature Evaluation. Scientific Reports, 2019; 9 (1) DOI: 10.1038/s41598-019-50686-z 

With the global epidemic that is climate change upon us. It is time for political leaders around the world to start taking notice and preparing plans to tackle this huge epidemic. One way we could look at this problem is from the perspective of game theory and Yoginder K Alagh even goes as far as to say this is where the solution lies. Intuitively, we would not think of tackling climate change in this approach but when we think of the major stakeholders in terms of climate change, then it makes a lot of sense. 

We have the big oil companies who do NOT want climate action to happen or else they lose a lot of money and then we have the other side of the spectrum of people who want to see a change. People who feel the effects of climate change want to see the world in a better place and want to see action. By looking at this problem from a game theory perspective, we can come up with nash equilibriums and find the best course of action. Of course, how would we justify the numbers? That is very hard to do and perhaps will take more time to justify. That being said, Berkeley has tackled game theory for climate change in the economic sense and has come to a few conclusions. Reducing global emissions is good, and no international agency can enforce environment agreements. It needs to be done by each country of their own.

So what does this mean for us in the future? Well, a step in the right direction is still a step and looking at things from different perspectives may find us an unexpected answer.

https://are.berkeley.edu/~traeger/Lectures/ClimateChangeEconomics/Slides/7%20International%20Cooperation%20-%201%20A%20Game%20Theoretic%20Perspective.pdf

https://www.financialexpress.com/opinion/climate-change-game-theory-holds-a-solution/1757991/

In class, we covered the topic of homophily and how it relates to the age, friendship count, and nationality of connections on Facebook. As expected, we found that the more people have in common with each other, the more likely they are to be friends. This result was obvious when looking at the race distribution of students in middle/high school, where students of the same race were more likely to connect with each other than with students of a different race. The phenomena of homophily in social networks, as seen in class, is applicable to many areas in life and is especially interesting when considered through the lens of dating.

In a study conducted by MIT, psychologists found that the more similar two potential romantic partners are, the more attractive they would be to each other and the more satisfaction both partners would have from their relationship (Fiore, Andrew & Donath, Judith, 2005). The study, conducted on an online dating site, showed that users selected partners with similar characteristics more often than chance would predict, which holds true for all of the characteristics that were analyzed. Moreover, the study found that users were more likely to respond to an initiation by a user that shared similarities with them.

Table 2 shows the characteristics that were evaluated in the study. An actual sameness percentage close to the expected sameness percentage indicates that users who communicated with each other with the shared characteristic did not communicate as often by chance as the researchers would have expected. A greater difference indicates that the users who shared a similar characteristic communicated much more often than expected.

The three most similar characteristics ( > 50% actual percent same) among people who found their partner on the dating site were: race, drinking habits, and marital status. The three least similar characteristics ( < 50% actual percent same) among people who found their partner on the dating site were: pets owned (not surprising), physical build, and education level. Keep in mind that the values for these characteristics are simply a measurement of the percentage of users that shared a characteristic; which is different than measuring which characteristic users found most attractive. In other words, a user in this system is more likely to date someone with a similar race with a less attractive physical appearance than date someone who is more physically attractive of a different race. 

These findings show a clear indication of homophily in the dating scene, which means that if you want to have a better chance at standing out to your crush, your best bet would be to explore the similarities that you share with him/her.

Links:

https://www.researchgate.net/publication/221518104_Homophily_in_online_dating_When_do_you_like_someone_like_yourself

Further discussion:

https://www.nytimes.com/2006/12/10/magazine/10Section2a.t-4.html

Reference:

Fiore, Andrew & Donath, Judith. (2005). Homophily in online dating: When do you like someone like yourself?. Conference on Human Factors in Computing Systems – Proceedings. 1371-1374. 10.1145/1056808.1056919.

With the 2019 Federal Election having recently taken place, the idea of strategic voting was observed. Strategic voting is basically where someone may vote for a candidate whom they may not necessarily want to win, but is a better option that someone else winning. Someone may strategically choose to vote, if they believe their candidate does not have a chance of winning. For example, take three parties Conservatives, Liberals, and the Green Party. If someone wanted the Green party to win, but the Green party did not have a high chance of winning, that person may instead choose to vote for Liberals for example, if they did not want the conservatives to win. While strategic voting may not have been the driving force for all voter’s decisions, it is an interesting idea to take a look at applied on a large scale, such as voting.

Voter’s who strategically voted, instead of simply voting for the candidate they wanted to win without thinking about other possible options, demonstrate the idea of game theory. Based on the article, Liberals benefited the most from strategic voting, and as such a sample scenario with be outlined where Liberals benefit from strategic voting.

For example, say we Conservatives have 50% support, Liberals have 49% support, and Green Party has 1% support. Without strategic voting and assuming every voter votes for the party they support, conservatives will win since they have the most support. However, imagine green supporters realize their party will not win, and strategically vote instead. Assume in this example, the voter would prefer the Liberal party to win over Conservatives.

We can assign numbers to represent how happy a voter will be if a party is elected.
Voter 1 (Supports Green party) -> Conservative = -5, Liberal = 0, Green = +5
Voter 2 (Supports Conservatives) -> Conservative = +5, Liberal = -5, Green = 0
Furthermore, assume that the background colour of the box represents the party who wins (Blue being Conservative and Red being Liberals). We can then define the game as such:

As we can see, a Conservative supporter will vote conservative, as their party does have a good chance of winning and therefore their vote will help conservatives win. However, a green party supporter who prefers Liberal over Conservative, may realize that voting Liberal instead of Green will be the better option. This is because as Green does not have a high chance of winning, and Liberal winning would be preferred over Conservatives winning.

Obviously the example outlined above, does not outline every possible scenario as there are other parties to consider, and the 2 voters can support different parties. Furthermore, not everyone will strategically vote. However, this does serve to outline how Game Theory applies to strategic voters, even if they may not be aware of it themselves.

References
https://nationalpost.com/news/politics/election-2019/liberals-benefited-most-from-strategic-voting-poll-of-late-deciding-voters-finds
https://www.cbc.ca/news/politics/poll-strategic-voting-1.5339692

Game theory is quite interesting topic and has a wide range of application in various fields ranging from math, business, to life sciences. Through this blog I would like to share an interesting application of Game theory. This is ‘Selection of sustainable municipal water reuse applications by multi-stakeholders using game theory’.          

This research was conducted by Gyan Chhipi-Shrestha, Manuel Rodriguez, Rehan Sadiq. The goal of the research was to successfully show how Game theory (combined with Multi-criteria decision Analysis – something which is not in scope of our course) can be used to solve the complex, conflict involving decision of water reuse. Water reuse means using the treated (i.e. making it safe for reuse) municipal waste-water (also known as reclaimed water) for various purposes such as toilet flushing, irrigating golf courses/ gardens/ parks, etc. How and where to use this reclaimed water has different impact on different group of stakeholders such as municipality, citizens and the farm operators, making sustainable selection of water reuse a complex decision.

The sustainable of water reuse was assessed under three criteria – environmental (ex – carbon footprint, fresh water issues, etc), economic (cost of maintaining the water infrastructure, etc.) and social (acceptance from citizens, health risks, etc.) After these evaluations and collecting data for these stakeholders, they came up with 8 options/applications of water reuse such as toilet flushing, agricultural irrigation, potable use, etc. They then converted this data into a payoff matrix for a 3-player game which looks as follows –

Since water reuse benefits the government as well as the citizens, they considered this game as a co-operative game i.e. like the coordination game as we saw in this week’s lecture. To reach to the solution of this game, they made use of Pareto optimality. A strategy say s is Pareto optimal ”if there does not exist other strategy that dominates s.” In this case optimality is reached with mutual sharing of costs by the stakeholders for a specific water reuse application. The research reached to a conclusion that municipality will have the benefit of $35/household/year and also the citizens needed to spend $100/household/year for the dual plumbing of toilet and lawn for reclaimed water.

Thus, it can be seen that how powerful and versatile the Game Theory is and can be used in various areas and can also be combined with other ways of analysis/concepts.

REFERENCE

Chhipi-Shrestha, G., Rodriguez, M., & Sadiq, R. (2019). Selection of sustainable municipal water reuse applications by multi-stakeholders using game theory. Science of The Total Environment, 650, 2512–2526. doi: 10.1016/j.scitotenv.2018.09.359

Over the past year, the world’s two largest economies have imposed tariffs on billions of dollars worth of one another’s goods. Since 2018, the US has imposed tariffs on more than $550bn of Chinese goods, and China has retaliated with tariffs on more than $185bn of US products. Washington delivered three rounds of tariffs last year, and a fourth one in September. The latest round targeted Chinese imports, from meat to musical instruments, with a 15% duty. Beijing has hit back with tariffs ranging from 5% to 25% on US goods. Negotiations are making slow progress but have proven ineffective and difficult. Washington plans to start a wave of new tariffs on Chinese goods, ranging from footwear to telephones in December. Unsurprisingly, China also plans to hit another 3,000 American products with tariffs by the end of the year. Both sides have threatened to take more action with new tariffs and increase existing duties in the coming months.

It has been universally acknowledged by almost every economist and investor that there is no winner in the trade campaign. And there are statistics revealed the tariff increases are estimated to reduce global trade volumes by around 6 percent and real GDP would drop by 1.4 percent, with US, China, and Europe each suffering a drop in output of 1.7-2.2 percent. If it is a war that everyone loses, what makes the negotiation being so tough and why would the US and China still repeatedly retaliate with tariffs against one another? The majority of economists highlight the connections between this tit-for-tat tariff game and the classic example of the prisoners’ dilemma.

In Gavyn Davies’ “Trade wars and the prisoners’ dilemma”, Davies successfully predicted that the economic damage in China would lead to retaliate by imposing higher tariffs on US goods and inevitably, the US would also suffer economic loses from China’s tariffs. It demonstrated that these countries are truly engaged in a prisoners’ dilemma game. Recall what we learned in the lecture about game theory, assume China and the US are two players who can either choose to increase tariffs or not. If the US applies tariff on China and China does not then China would get hurt; similarly, if China imposes tariff but the US does not retaliate, then the US would get hurt. Since each of them wants to maximize its self-interests which leads to both the US and China adopt protectionism by imposing higher tariffs. It is predictable that they will likely end up in a bad “Nash” equilibrium if they continue to retaliate although they can reach a win-win situation if they were to simply cooperate with each other. Davies forecast it’s likely that there will be a 1-3% reduction in global output in the next several years if all countries continue to choose to adopt protectionism strategies that retaliate with higher tariffs to protect self-interests in a time of uncertainty.

Historical experience has also proved that raising tariffs for the sake of domestic interests alone can not necessarily achieve the purpose of preventing the outflow of domestic consumption and protecting employment, and sometimes it even backfired. In the current situation of trade friction, it is necessary for both parties to jump out of their own interests and proceed from the overall situation in order to achieve optimal equilibrium. However, if the US and China can not reach an agreement in the next few years, are we just going to watch the global economy keep going down? There’s no way we can get out of this vicious trade war circle? There is an organization called “The World Trade Organization” (WTO) exists for many years. WTO is aimed to safeguard basic principles of international trade, such as no discrimination, reciprocity, transparency. Moreover, it provides the dispute resolution process in case of a conflict. Hopefully, WTO would play its part in this trade war and could manage to change Donald Trump’s opinion on how easy it is to win the trade war without damaging the US itself.

Reference:

https://www.china-briefing.com/news/the-us-china-trade-war-a-timeline/

https://www.bbc.com/news/business-48196495

https://seekingalpha.com/article/4263591-u-s-china-prisoners-dilemma

https://www.ft.com/content/d288a98e-2e90-11e8-9b4b-bc4b9f08f381

“Do not use Wikipedia. It is unreliable.” All through high school and even in the higher grades of elementary school, every time there was an assignment that involved research the teacher would constantly remind the class those unforgettable words. If it is so unreliable then why is it such a popular website?  Haven’t you always noticed that Wikipedia is always one of the top links in all searches? Its because with Google’s support, Wikipedia constantly appears whenever a search is conducted on Google Search, which has helped it to acquire over 300 million readers worldwide.  Many digital marketers use this popularity of Wikipedia to boost their clients’ businesses.  There is more to Wikipedia than just a reference source that teachers used to, and still, disapprove of.

What makes Wikipedia so desirable to digital marketers, such as ‘Legalmorning’ and ‘Colorado Digital Experts’, has to do with the concept of PageRanks as we learned in class. As of now, tens of millions of links are in-linked to Wikipedia, which in turn gives the website a very high PageRank, since we know that a page that is linked to by many pages with high PageRank receives a high rank itself. Because of this, many people are able to exploit Wikipedia by creating a Wiki article with an out-link to their own website. This is very useful as that website would obtain a percentage of the votes from Wikipedia, where even though that percentage is probably extremely small due to the sheer amount of out-links from Wikipedia, it would still be significant and help their website by making the link more important and likely to be included as part of Google search results.

An example of this (as described by https://blog.ispionage.com/wikipedia-affects-pagerank.html) is when “Luck of the Legion” is searched in Google, the website DanDare.org shows up and is above even Amazon in terms of PageRank.

This was because, in Wikipedia, an article about “Luck of the Legion” had a reference to a page in DanDare.org. By associating with Wikipedia, the websites that are referenced become part of top search results because of how the PageRank algorithm works, which is very interesting to me.

Its also because of this that digital marketers find that Wikipedia is very profitable for them. They can use Wiki to embed an out-link to their client’s website within new articles they can create or into pre-existing ones. By doing this, they claim that by including their clients’ link within Wikipedia, it can help to improve their clients’ PageRanks, which is likely to be true. 

It would be great for digital marketers or any companies wishing to improve their exposures to help increase their businesses to just link with Wikipedia, but it may not be that simple.  Wikipedia had implemented a no-follow policy for certain links to help discourage the website from being used by people to market their products. Yet, even these links that have the no-follow tags to them still have some importance during a search though not as much as the do-follow links.  There are also rules and certain standards that a Wikipedia article must uphold to which makes it even harder to be linked with the website.  There are companies offering to create Wikipedia articles for clients by promoting Wikipedia’s ability to increase their PageRanks.

In my opinion, even if a Wikipedia article was perfectly written and had all the needed out-links embedded within it, it doesn’t necessarily mean there will be an improvement in business.  Considering there must be millions of Wikipedia articles on the internet, then the chances of having a particular article showing up in the results especially on the first page are pretty slim.  If the article is hardly accessed then the PageRank for the backlinks may not increase. Yet, Wikipedia appears to still be a popular site by which digital marketers can increase the PageRanks of out-links and thus promote their clients’ websites.

As an aside, even giant companies, such as YouTube and Facebook, plan to associate with Wikipedia, which implies that these big businesses consider the website to be reliable.  They want their users to have a reference source to access in order to verify any content that they encounter on their sites.  

Relevant Links

• https://blog.ispionage.com/wikipedia-affects-pagerank.html
  
• https://medium.com/@coloradodigitalexperts/wikipedia-seo-strategies-how-wiki-links-affect-your-google-ranking-2fb0d2e034ad
  
• https://www.wired.co.uk/article/wikipedia-google-youtube-facebook-support

Reference List

Colorado Digital. (2019, July 2). Wikipedia SEO Strategies: How Wiki Links Affect Your Google Ranking? Retrieved November 7, 2019, from https://medium.com/@coloradodigitalexperts/wikipedia-seo-strategies-how-wiki-links-affect-your-google-ranking-2fb0d2e034ad.

Maher, K. (2018, June 15). Facebook and Google must do more to support Wikipedia. Retrieved November 7, 2019, from https://www.wired.co.uk/article/wikipedia-google-youtube-facebook-support.

Wood, M. (n.d.). Pro SEO Tip: How WikiPedia Can Affect Your PageRank Score. Retrieved November 7, 2019, from https://blog.ispionage.com/wikipedia-affects-pagerank.html.